The moderating role of artificial intelligence on the relationship between knowledge management and employees innovative work behavior

Purpose This study aims to examine how effective knowledge management (KM) practices drive employee innovative work behavior (EIWB) across the dimensions of idea generation (IG), idea promotion (IP) and idea realization (IR), and investigates the moderating role of artificial intelligence (AI) within this relationship. Design/methodology/approach Using a quantitative research design, data was collected via an online survey using convenience sampling among employees across various industries in Lebanon and the GCC region. The study analyzed responses from 160 participants using partial least squares structural equation modeling with SmartPLS software to test the proposed hypotheses. Findings The results demonstrate that robust KM practices significantly enhance EIWB across all innovation dimensions. However, the moderating effects of AI are weak and inconsistent, indicating that current AI applications have a limited impact on enhancing the knowledge-sharing processes essential for fostering innovation. Research limitations/implications The study is limited by its cross-sectional design and the use of convenience sampling, which may restrict the generalizability of the findings. Future research should consider longitudinal designs and more diverse geographic samples to validate and extend these insights. Originality/value This research uniquely integrates the fields of KM, AI and EIWB by exploring the nuanced interplay between human-centric knowledge sharing and emerging AI technologies. The study provides valuable theoretical and practical insights for organizations seeking to balance technological advancements with human innovation to maintain a competitive edge in a knowledge-driven economy.